The Philosophy of Data Science: Data Science Governance

An event co-sponsored by the Centre for Human & Machine Intelligence (HMI),
Frankfurt School of Finance & Management and part of the project group Regulatory Theories of Artificial Intelligence of the Centre Responsible Digitality (ZEVEDI)

This conference, hosted by the Centre for Human & Machine Intelligence (HMI) at the Frankfurt School of Finance & Management and part of the project group Regulatory Theories of Artificial Intelligence of the Centre Responsible Digitality (ZEVEDI), aims to bring together researchers from ethics, political philosophy, and philosophy of science to discuss questions surrounding the governance of data science. The conference’s guiding question is how to conduct, design and regulate data science for the public good. The proper guidance of data science requires the formulation of both moral and legal norms and frameworks, which may guide individuals, private corporations, as well as public and political institutions. The conference will approach this topic by looking at a range of different domains, exploring the specific challenges they raise and how they might call for different, custom-made solutions. These domains include, but are not limited to, healthcare, scientific research, transportation, surveillance, social media, and law and law enforcement. In these domains, good data science governance is a matter of understanding and balancing a variety of often competing values and ideals, among which are responsibility, trust, fairness, accountability, privacy, cost-efficiency, as well as epistemic goods such as knowledge, understanding and predictive power.